Apple's new ARM CPUs vs, classic x86 for physics?

In summary, the author is looking to replace their computer and is considering two options, a Mac or a Windows laptop. They note that the Macs are compatible with a few software titles, but the Windows laptops are not compatible with some titles. They recommend looking at what the price of an M1 Mac would get you in desktop hardware with as much screen real estate as you can afford.
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Dex_
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ARM vs x86. Which is more compatible with Physics software?
Hi it's my first post here!
I'm in my second year of my degree and looking to replace my computer. The new M-series chips seem like a better deal, however I am nervous that some software that might not be compatible with the ARM architecture. For more context on my workflow I do quite a bit of coding and use MacTeX for my lab reports.

Should I go with the Macs or buy a Windows laptop?
 
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What "physics software" are you looking at, and what does it say about requirements?
 
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When I upgraded to Apple Silicon awhile back, I didn't have to abandon any software due to compatibility. The current version of MacTeX runs natively on ARM, and I'm pretty sure the previous one did too. The only software I stopped using was DropBox since they still hadn't bothered to release an ARM client at the time and I didn't really use DropBox anymore anyway. The ARM-based systems have been out for a while now, so I would expect most developers who support macOS have already ported their software to Apple Silicon.
 
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@Vanadium 50 I'm still an undergraduate so I've not used a lot of the heavy programs. The ones I use right now are python libraries such at matplot, pandas, astropy and numpy obviously. Our university uses the Anaconda distribution, but my computer can't handle it so I am forced to use Spyder and download some of the libraries myself. Other than python, we have used MATLAB before and I regularly have to use SAOImageDS9.
 
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Dex_ said:
Our university uses the Anaconda distribution, but my computer can't handle it so I am forced to use Spyder and download some of the libraries myself.
You might want to check out compatibility of all of Anaconda on M1 https://www.anaconda.com/blog/new-release-anaconda-distribution-now-supporting-m1
Please note that macOS M1 does not support Qt yet – Anaconda Navigator and Spyder will not be available. Please check back for updates.
Support for other Python things on Apple Silicon (e.g. TensorFlow) is also more complicated.

As an alternative have you looked at what the price of an M1 Mac would get you in (possibly refurbished) desktop hardware with as much screen real estate as you can afford (possibly starting small and upgrading later)? You can still use your laptop for taking notes in class etc, or if it is really dying get a chromebook.

IME expensive laptops suck for coding, writing documents, spreadsheets, just about everything apart from showing off in coffee shops next to a power outlet.
 
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1. How do Apple's new ARM CPUs compare to classic x86 processors for physics-based tasks?

The new Apple ARM CPUs have proven to be competitive with classic x86 processors for physics-based tasks. In fact, early benchmarks have shown that for certain tasks, the ARM CPUs actually outperform the x86 processors. This is due to the design of the ARM architecture, which focuses on energy efficiency and parallel processing.

2. Will the switch to ARM CPUs affect the performance of physics simulations and calculations?

It is possible that some physics simulations and calculations may experience a slight decrease in performance during the transition to ARM CPUs. However, this is expected to be temporary as software developers optimize their programs for the new architecture. In the long run, the ARM CPUs are expected to offer comparable or even improved performance for physics-based tasks.

3. How will the use of ARM CPUs impact the software and tools commonly used in physics research?

The transition to ARM CPUs may require some software and tools to be recompiled or updated for compatibility. However, many popular physics software programs and tools already have versions that are compatible with ARM processors. Additionally, Apple has developed a new software translation tool, Rosetta 2, which allows x86 programs to run on ARM-based Macs without any loss in performance.

4. Are there any potential advantages to using ARM CPUs for physics research?

One potential advantage of using ARM CPUs for physics research is the increased energy efficiency and lower power consumption. This can be especially beneficial for large-scale simulations or calculations that require significant computing power. Additionally, ARM processors are known for their ability to handle parallel processing, which can be useful for certain types of physics tasks.

5. Will the switch to ARM CPUs affect the overall cost of physics research?

It is difficult to predict the exact impact on the cost of physics research with the switch to ARM CPUs. However, it is expected that the lower power consumption and potential performance improvements of ARM processors could ultimately result in cost savings for researchers. Additionally, the transition is not expected to require significant hardware upgrades or changes, which could also help keep costs down.

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